Summary of Detecting Emotional Incongruity Of Sarcasm by Commonsense Reasoning, By Ziqi Qiu et al.
Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning
by Ziqi Qiu, Jianxing Yu, Yufeng Zhang, Hanjiang Lai, Yanghui Rao, Qinliang Su, Jian Yin
First submitted to arxiv on: 17 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel framework for sarcasm detection, called EICR, which leverages commonsense augmentation and incongruity reasoning to improve performance in complex real-world scenarios. The framework employs retrieval-augmented large language models to supplement missing background knowledge, constructs a dependency graph to capture contextual associations, and introduces an adaptive reasoning skeleton to extract sentiment-inconsistent subgraphs. Adversarial contrastive learning is also employed to enhance the robustness of the detector. Experiments on five datasets demonstrate the effectiveness of EICR in detecting sarcasm. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers better understand when people are being sarcastic or mean-spirited. Right now, computer programs aren’t very good at catching sarcasm because they don’t have common sense like humans do. To fix this problem, the researchers created a new way to detect sarcasm called EICR. It uses large language models and graph theory to understand the relationships between words in a sentence and figure out if someone is being sarcastic or not. The results show that this new method works better than existing methods on five different datasets. |
